Estimating the parking demand of free-floating bike sharing: A journey-data-based study of Nanjing, China. (20th January 2020) - Hua, Mingzhuang; Chen, Xuewu; Zheng, Shujie; Cheng, Long; Chen, Jingxu
Abstract: In recent years, free-floating bike sharing (FFBS) has been rapidly promoted in China, attracting numerous users and consuming many resources. The extensive supply and inefficient repositioning of FFBS are challenges for sustainable development, and put forward higher requirements for parking planning. This paper estimates the parking demand of all three FFBS companies by combining the journey data of Mobike in Nanjing and the Nanjing FFBS bike survey. Three clustering methods were applied to determine the virtual stations of bike aggregation. The maximum number of bikes in a day is recognized as the parking demand in each virtual station. The results show that more than half of bikes are in low turnover rate, and the management of FFBS should be improved. The K-means method turns out to observe the best clustering result for determining virtual stations. The demand for parking spaces of all FFBS companies in Nanjing is estimated accordingly. In addition, the relations of bicycle supply, repositioning and parking are discussed, showing the impact of parking demand on greenhouse gas (GHG) emissions. The research could help to propose an appropriate plan for meeting FFBS parking demand, and have enlightening sight of emissions reduction and sustainable development in the FFBS services.